Stochastic models | Monte Carlo methods in finance | Actuarial science

Stochastic modelling (insurance)

"Stochastic" means being or having a random variable. A stochastic model is a tool for estimating probability distributions of potential outcomes by allowing for random variation in one or more inputs over time. The random variation is usually based on fluctuations observed in historical data for a selected period using standard time-series techniques. Distributions of potential outcomes are derived from a large number of simulations (stochastic projections) which reflect the random variation in the input(s). Its application initially started in physics. It is now being applied in engineering, life sciences, social sciences, and finance. See also Economic capital. (Wikipedia).

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Basic stochastic simulation b: Stochastic simulation algorithm

(C) 2012-2013 David Liao (lookatphysics.com) CC-BY-SA Specify system Determine duration until next event Exponentially distributed waiting times Determine what kind of reaction next event will be For more information, please search the internet for "stochastic simulation algorithm" or "kin

From playlist Probability, statistics, and stochastic processes

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"Data-Driven Optimization in Pricing and Revenue Management" by Arnoud den Boer - Lecture 1

In this course we will study data-driven decision problems: optimization problems for which the relation between decision and outcome is unknown upfront, and thus has to be learned on-the-fly from accumulating data. This type of problems has an intrinsic tension between statistical goals a

From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management​

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Applied Math Perspectives on Stochastic Climate Models ( 2 ) - Andrew J. Majda

Lecture 2: Applied Math Perspectives on Stochastic Climate Models Abstract: We are entering a new era of Stochastic Climate Modeling. Such an approach is needed for several reasons: 1) to model crucial poorly represented processes in contemporary comprehensive computer models such as inte

From playlist Mathematical Perspectives on Clouds, Climate, and Tropical Meteorology

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“Data-Driven Pricing” – Prof. Omar Besbes

Pricing is central to many industries and academic disciplines ranging from Operations Research to Economics and Computer Science. At the heart of pricing lies a fundamental informational dimension regarding the level of knowledge about customers' values. In practice, the latter comes from

From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management​

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"Diffusion Approximation and Sequential Experimentation" by Victor Araman

We consider a Bayesian sequential experimentation problem. We identify environments in which the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regimes, we derive a diffusion approximation f

From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management​

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Iterative stochastic numerical methods for statistical sampling: Professor Ben Leimkuhler

I study the design, analysis and implementation of algorithms for time-dependent phenomena and modelling for problems in engineering and the sciences. My previous works have helped to establish the foundations of molecular simulation, providing efficient deterministic and stochastic numeri

From playlist Data science classes

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Stochastic Normalizing Flows

Introduction to the paper https://arxiv.org/abs/2002.06707

From playlist Research

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Fourteenth SIAM Activity Group on FME Virtual Talk

Speakers: Damir Filipovic, EPFL and Swiss Finance Institute Title: A Machine Learning Approach to Portfolio Pricing and Risk Management for High-Dimensional Problems Moderator: Rene Carmona, Princeton University

From playlist SIAM Activity Group on FME Virtual Talk Series

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Financial Options Pricing History. How do Investors Price Options?

Financial Options Pricing History. Today we will learn How do Investors Price Options? These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0 Check out our website http://www.onfinance.org/ Follow Patri

From playlist Class 2: An Introduction to Options

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4 2 Risk neutral pricing Part 1

BEM1105x Course Playlist - https://www.youtube.com/playlist?list=PL8_xPU5epJdfCxbRzxuchTfgOH1I2Ibht Produced in association with Caltech Academic Media Technologies. ©2020 California Institute of Technology

From playlist BEM1105x Course - Prof. Jakša Cvitanić

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Francois Baccelli: High dimensional stochastic geometry in the Shannon regime

This talk will focus on Euclidean stochastic geometry in the Shannon regime. In this regime, the dimension n of the Euclidean space tends to infinity, point processes have intensities which are exponential functions of n, and the random compact of interest sets have diameters of order squa

From playlist Workshop: High dimensional spatial random systems

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IMS Public Lecture: What Really Happened in 2008, and Why?

Philip Protter, Columbia University

From playlist Public Lectures

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Stochastic modelling of geophysical flows - Mémin - Workshop 2 - CEB T3 2019

Mémin (INRIA, FR) / 13.11.2019 Stochastic modelling of geophysical flows ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/ Twitter : https://twitter.com/InHe

From playlist 2019 - T3 - The Mathematics of Climate and the Environment

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Dylan Possamaï: Principal Agent Modelling - lecture 1

CIRM HYBRID EVENT These lectures will consist in an overview of recent progresses made in contracting theory, using the so-called dynamic programming approach. The basic situation is that of a Principal wanting to hire an Agent to do a task on his behalf, and who has to be properly incenti

From playlist Probability and Statistics

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Tony Lelievre (DDMCS@Turing): Coarse-graining stochastic dynamics

Complex models in all areas of science and engineering, and in the social sciences, must be reduced to a relatively small number of variables for practical computation and accurate prediction. In general, it is difficult to identify and parameterize the crucial features that must be incorp

From playlist Data driven modelling of complex systems

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Stanford Seminar - Entrepreneurial Thought Leaders: Hemant Shah of Risk Management Solutions

Hemant Shah Risk Management Solutions In this seminar, entrepreneurial leaders share lessons from real-world experiences across entrepreneurial settings. Speakers include entrepreneurs, leaders from global technology companies, venture capitalists, and best-selling authors. Half-hour talk

From playlist MS&E472 - Entrepreneurial Thought Leaders - Stanford Seminars

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"Data-Driven Optimization in Pricing and Revenue Management" by Arnoud den Boer - Lecture 3

In this course we will study data-driven decision problems: optimization problems for which the relation between decision and outcome is unknown upfront, and thus has to be learned on-the-fly from accumulating data. This type of problems has an intrinsic tension between statistical goals a

From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management​

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Application of Time Series Analysis to Finance by Sankarshan Basu

Program Summer Research Program on Dynamics of Complex Systems ORGANIZERS: Amit Apte, Soumitro Banerjee, Pranay Goel, Partha Guha, Neelima Gupte, Govindan Rangarajan and Somdatta Sinha DATE : 15 May 2019 to 12 July 2019 VENUE : Madhava hall for Summer School & Ramanujan hall f

From playlist Summer Research Program On Dynamics Of Complex Systems 2019

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Understanding Discrete Event Simulation, Part 3: Leveraging Stochastic Processes

Watch more MATLAB Tech Talks: https://goo.gl/ktpVB7 Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn how discrete-event simulation uses stochastic processes, in which aspects of a system are randomized, in this MATLAB®

From playlist Understanding Discrete-Event Simulation - MATLAB Tech Talks

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Optimal Transport Methods and Applications to Statistics and... (Lecture 2) by Jose Blanchet

PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear

From playlist Advances in Applied Probability 2019

Related pages

Random variable | Monte Carlo method | Mean | Percentile | Reinsurance | Wilkie investment model | Probability distribution | Probability density function | Economic capital | Stochastic | Stochastic investment model | Stochastic process